Triple
T18265950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The METAFONTbook |
E437483
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Addison-Wesley |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Addison-Wesley | Statement: [The METAFONTbook, publisher, Addison-Wesley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Addison-Wesley Context triple: [The METAFONTbook, publisher, Addison-Wesley]
-
A.
Addison-Wesley
chosen
Addison-Wesley is a prominent American publishing company known for its influential textbooks and professional books in science, engineering, and computer science.
-
B.
Morgan Kaufmann
Morgan Kaufmann is a prominent academic and professional publishing imprint known for influential books in computer science and engineering.
-
C.
Wiley
Wiley is a small unincorporated rural community located in Prowers County in southeastern Colorado.
-
D.
Wiley
Wiley is a masculine given name, often associated with notable American figures such as aviator Wiley Post.
-
E.
Wiley
Wiley is a pioneering British grime MC and producer, often dubbed the "Godfather of Grime" for his foundational role in shaping the genre.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7af85c81909859e7247738a535 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.